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Modeling neuronal cell and networks

Coordination : David Holcman, Biology Department, ENS

Format : Hours : 45h. One course per week. Beginning : October (during around 4 months)

Crédit : 6 ECTS

Semester : 1st semestre
Number of students :

Présentation :
Themes :
Part I : Diffusion in microdomains : modeling, analysis, stochastic
processes, MFPT, see Bionewmetrics

Part II : Modeling neuronal cells and network :
1-Introduction of the HH-model for neuronal excitability.
2-Mean field model of synaptic depression.
3- Modeling and simulations of a neural network that generates a clock :
example of the PreBotz complex.
4- Method to extract synaptic connectivity from the statistics of time
series (electrophysiological recordings).
5-Diffusion during synaptic transmission
5a- Computing the probability of vesicular release.
5b- Asymptotic computations.

Part III : Modeling phototransduction
1-Model of rhodopsin activation/ deactivation.
2-Markov chains for the dynamics of PDE molecules.
3-Computing the rate of cGMP hydrolysis.
4-Mode of diffusion including the geometry of the outersegment.
5-Simulations of the full photoresponse.
6-Open questions in fly photoreceptors, olfaction, hair cells.

Teaching team : David Holcman (ENS, Paris)

Exams : small projects, with a report and oral presentation (30 minutes).